outlier-scan

Community

Multi-method outlier detection with JSON reports.

Authorhaomingz
Version1.0.0
Installs0

System Documentation

What problem does it solve?

CSV data often contains outliers that distort analysis and complicate data quality assessments. This tool detects outliers using Z-score, IQR, and moving-average methods, then categorizes them for targeted review and reporting.

Core Features & Use Cases

  • Multi-method anomaly detection using Z-score, IQR, and moving-average to cover different data distributions.
  • Automatic labeling of anomalies as "explainable" or "needs_attention" to prioritize investigation.
  • JSON report summarizing per-row details and column statistics for downstream analysis and dashboards.
  • Use case: sensor streams, finance data, or any tabular dataset where outliers matter.

Quick Start

Run python3 scripts/anomaly_detector.py data.csv to detect outliers across numeric columns and generate a JSON report.

Dependency Matrix

Required Modules

None required

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: outlier-scan
Download link: https://github.com/haomingz/kimi-skills/archive/main.zip#outlier-scan

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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